中国邮电高校学报(英文) ›› 2022, Vol. 29 ›› Issue (2): 24-32.doi: 10.19682/j.cnki.1005-8885.2022.0013

所属专题: 文化计算专题

• Special Topic: Cultural Computing • 上一篇    下一篇

Research on sentiment terms extraction and visualization of character sentimental interactions in A Dream of Red Mansions

黄佩,张萌,万柳,雷轩铮   

  1. 北京邮电大学
  • 收稿日期:2022-01-18 修回日期:2022-03-20 出版日期:2022-04-26 发布日期:2022-04-26
  • 通讯作者: 黄佩 E-mail:huangpei@bupt.edu.cn
  • 基金资助:
    个性化推荐平台的文化传播模式创新研究

Research on sentiment terms extraction and visualization of character sentimental interactions in A Dream of Red Mansions

  • Received:2022-01-18 Revised:2022-03-20 Online:2022-04-26 Published:2022-04-26
  • Supported by:
    Research on Cultural Communication Innovation in Personal Recommendation Platform

摘要:

In the context of interdisciplinary research, using computer technology to further mine keywords in cultural texts and carry out semantic analysis can deepen the understanding of texts, and provide quantitative support and evidence for humanistic studies. Based on the novel A Dream of Red Mansions, the automatic extraction and classification of those sentiment terms in it were realized, and detailed analysis of large-scale sentiment terms was carried out. Bidirectional encoder representation from transformers (BERT) pretraining and fine-tuning model was used to construct the sentiment classifier of A Dream of Red Mansions. Sentiment terms of A Dream of Red Mansions are divided into eight sentimental categories, and the relevant people in sentences are extracted according to specific rules. It also tries to visually display the sentimental interactions between Twelve Girls of Jinling and Jia Baoyu along with the development of the episode. The overall F1 score of BERT-based sentiment classifier reached 84-89%. The best single sentiment score reached 91-15%. Experimental results show that the classifier can satisfactorily classify the text of A Dream of Red  Mansions, and the text classification and interactional analysis results can be mutually verified with the text interpretation of A dream of Red Mansions by literature experts.

关键词: 红楼梦|情感词抽取|角色情感互动|BERT预训练模型|数据可视化

Abstract:

In the context of interdisciplinary research, using computer technology to further mine keywords in cultural texts and carry out semantic analysis can deepen the understanding of texts, and provide quantitative support and evidence for humanistic studies. Based on the novel A Dream of Red Mansions, the automatic extraction and classification of those sentiment terms in it were realized, and detailed analysis of large-scale sentiment terms was carried out. Bidirectional encoder representation from transformers (BERT) pretraining and fine-tuning model was used to construct the sentiment classifier of A Dream of Red Mansions. Sentiment terms of A Dream of Red Mansions are divided into eight sentimental categories, and the relevant people in sentences are extracted according to specific rules. It also tries to visually display the sentimental interactions between Twelve Girls of Jinling and Jia Baoyu along with the development of the episode. The overall F1 score of BERT-based sentiment classifier reached 84-89%. The best single sentiment score reached 91-15%. Experimental results show that the classifier can satisfactorily classify the text of A Dream of Red  Mansions, and the text classification and interactional analysis results can be mutually verified with the text interpretation of A dream of Red Mansions by literature experts.

Key words: A Dream of Red Mansions| sentiment term extraction| character sentiment interaction| BERT| data visualization